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To users of NAG Library Documentation - MathJax

The NAG Library documentation makes use of the MathML format for displaying mathematics within web pages. This is supported natively in the Firefox browser, but for users of other browsers we use the freely available MathJax javascript library. Unfortunately the MathJax consortium is having to shut down its server as detailed here. As detailed in that page, users may instead use a locally installed copy of MathJax, or may use a different freely available server.

The copies of the NAG Library documentation on our website have already been updated, for example Fortran Library Documentation and C Library Documentation.

However, if you have a locally downloaded copy of the Fortran or C Library Documentation (NAG Toolbox for MATLAB® documentation is not affected) then you will need to change the file:

html/styles/nagmathml.js

and change line 4 to refer to a new location for MathJax.

The existing line is:

var nagmathjax= ((window.location.protocol=="https:") ? "https" : &…

The women that helped create NAG - International Women's Day 2017

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On International Women’s Day 2017 we are proud to highlight three pivotal women that played important roles in forming the Numerical Algorithms Group (NAG). 

NAG has been producing numerical software for over 4 decades which is a remarkable achievement given how hardware and algorithms have evolved during this time. Back in 1970 four people got together: Brian Ford, Lecturer at the University of Nottingham (later to become NAG Founder Director); Joan Walsh, University Reader in Numerical Analysis at the University of Manchester and expert on Ordinary Differential Equations; Shirley Lill, Lecturer in Optimization at the University of Leeds; and Linda Hayes, knowledgeable in Numerical Linear Algebra, and Research Assistant of Professor Leslie Fox (Director of the University of Oxford Computing Laboratory and Professor of Numerical Analysis). 

At this historic meeting on the 13 May 1970, Joan, Shirley, Linda, and Brian discussed their institutions new ICL 1906A Computers and the disti…

New Mathematical Optimization Collaboration with the University of Oxford

NAG has recently started an academic collaboration with the Centre for Doctoral Training in Industrially Focused Mathematical Modelling (InFoMM) at the University of Oxford. Lindon Roberts is the main researcher supervised by Coralia Cartis, Associate Professor in Numerical Optimization. NAG is a strong supporter of InFoMM, offering student projects, providing training courses and sitting on the Industrial Engagement Committee. This project focuses on mathematical optimization where derivatives are not readily available, so called derivative-free optimization (DFO). It is not easy or even possible to evaluate derivatives of functions which appear in the optimization model and thus many well-established approaches in mathematical optimization might not be satisfactory. Moving to a derivative-free regime presents novel approaches for approximating the solution without computing or estimating derivatives. NAG added its first derivative-free solver to the NAG Library about five years ago. …

The New NAG Optimization Modelling Suite

Nowadays a vast majority of optimization solvers can handle very complex problems involving many variables and various types of the constraints with a different structure. Designing an interface for such a solver, which would allow a complex input without compromising the ease of use, is challenging. A new suite of routines, the NAG Optimization Modelling Suite, has been introduced in Mark 26 of the NAG Library to tackle the input of complex problems without forming difficult interfaces with a daunting number of arguments. The suite is used by the new optimization solvers introduced at this mark; the semidefinite programming solver and the interior point method for nonlinear optimization. The suite will expand in the years to come to handle more problem types. The main aim of the NAG Optimization Modelling Suite is the ability to define and solve various optimization problems in a uniform manner. There are three key features of the suite. Firstly, the definition of the optimization p…

Calling NAG Routines from Julia

Julia Computing was founded in 2015 by the co-authors of the Julia programming language to help private businesses, government agencies and others develop and implement Julia-based solutions to their big data and analytics problems. Julia is an open-source language for high-performance technical computing created by some of the best minds in mathematical and statistical computing. Reid Atcheson, Accelerator Software Engineer, NAG, and Andy Greenwell, Senior Application Engineer, Julia Computing, have teamed up to ensure that NAG Library routines can be called from the Julia language. Read their piece here.

Fortran Modernisation Workshop - An Attendee's Perspective

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Jonathan Cooper, Research Lecturer, Department of Computer Science at The University of Oxford recently attended a Fortran Modernisation Workshop and has posted about the day: This two day intense workshop covered a vast array of topics related to developing reliable computational science software in Fortran more effectively, yet still retained time for practical work trying these out and discussions between the course leaders and participants. It was attended by 31 students and staff members of the University. Wadud Miah (NAG) led the workshop, assisted in lecturing by Fatima Chami (Durham) and Kyle Fernandes (Cambridge). Wadud began by arguing for the importance of good software engineering practices in computational science, then gave a potted history of Fortran culminating with a tour through the features in recent versions of the standard that facilitate writing good code. Sessions also covered supporting tools that enable good development practices, including a brief guest lectu…

Analysis of performance optimisation service requests: what kind of codes are we helping as part of POP CoE?

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by Sally Bridgwater, NAG HPC Application Analyst

NAG is a partner in the Performance Optimisation and Productivity Centre of Excellence (POP). POP was created with the aim of boosting the productivity of EU research and industry by providing free of charge services to advise on improving the performance of high performance computing (HPC) parallel software.

The POP team consists of six partner organisations from Germany, France, Spain and the UK. Over 30 codes have applied for the POP service so far since its kick-off in October 2015. I decided to have a look into the details of what types of codes POP is working with and see if any interesting themes emerge. Since this is quite early in the project it will be useful to revisit and see how it evolves over time.

First I decided to look at what languages all of the codes were written in. From my experience in Physics, I generally assumed that Fortran was the most prevalent language in academic/scientific applications.


This seems to be the…